Publications associées à Structured Query Language

Aggregation and Exploration of High-Dimensional Data Using the Sudokube Data Cube Engine

Christoph Koch, Sachin Basil John, Zhekai Jiang, Peter Lindner

We present Sudokube, a novel system that supports interactive speed querying on high-dimensional data using partially materialized data cubes. Given a storage budget, it judiciously chooses what projections to precompute and materialize during cube constru ...

Association for Computing Machinery2023

LAQy: Efficient and Reusable Query Approximations via Lazy Sampling

Anastasia Ailamaki, Viktor Sanca, Periklis Chrysogelos

Modern analytical engines rely on Approximate Query Processing (AQP) to provide faster response times than the hardware allows for exact query answering. However, existing AQP methods impose steep performance penalties as workload unpredictability increase ...

2023

Interactive-time Exploration, Querying, and Analysis of Large High-dimensional Datasets

Sachin Basil John

In the current era of big data, aggregation queries on high-dimensional datasets are frequently utilized to uncover hidden patterns, trends, and correlations critical for effective business decision-making. Data cubes facilitate such queries by employing p ...

EPFL2023

Efficient and Effective Multi-Modal Queries Through Heterogeneous Network Embedding

Karl Aberer, Quoc Viet Hung Nguyen, Thanh Trung Huynh, Thành Tâm Nguyên, Chi Thang Duong

The heterogeneity of today's Web sources requires information retrieval (IR) systems to handle multi-modal queries. Such queries define a user's information needs by different data modalities, such as keywords, hashtags, user profiles, and other media. Rec ...

IEEE COMPUTER SOC2022

Sampling-Based AQP in Modern Analytical Engines

Anastasia Ailamaki, Viktor Sanca

As the data volume grows, reducing the query execution times remains an elusive goal. While approximate query processing (AQP) techniques present a principled method to trade off accuracy for faster queries in analytics, the sample creation is often consid ...

ACM2022

Efficient Massively Parallel Join Optimization for Large Queries

Anastasia Ailamaki, Bikash Chandra, Srinivas Karthik Venkatesh, Riccardo Mancini, Vasileios Mageirakos

Modern data analytical workloads often need to run queries over a large number of tables. An optimal query plan for such queries is crucial for being able to run these queries within acceptable time bounds. However, with queries involving many tables, find ...

ACM2022

Edit Based Grading of SQL Queries

Bikash Chandra

Grading student SQL queries manually is a tedious and error-prone process. Earlier work on testing correctness of student SQL queries, such as the XData system, can be used to test the correctness of a student query. However, in case a student query is fou ...

ASSOC COMPUTING MACHINERY2021

Taster: Self-Tuning, Elastic and Online Approximate Query Processing

Anastasia Ailamaki, Raja Appuswamy, Matthaios Alexandros Olma, Odysseas Papapetrou

Current Approximate Query Processing (AQP) engines are far from silver-bullet solutions, as they adopt several static design decisions that target specific workloads and deployment scenarios. Offline AQP engines target deployments with large storage budget ...

IEEE2019

Efficient Bundled Spatial Range Queries

Anastasia Ailamaki, Darius Sidlauskas, Thomas Heinis, Eleni Tzirita Zacharatou, Farhan Tauheed

Efficiently querying multiple spatial data sets is a growing challenge for scientists. Astronomers query data sets that contain different types of stars (e.g., dwarfs, giants, stragglers) while neuroscientists query different data sets that model different ...

ASSOC COMPUTING MACHINERY2019

Interferometric synthetic aperture microscopy for extended focus optical coherence microscopy

Theo Lasser, Paul James Marchand, Arno Pino Bouwens, Jérôme Extermann, Séverine Coquoz

Optical coherence microscopy (OCM) is an interferometric technique providing 3D images of biological samples with micrometric resolution and penetration depth of several hundreds of micrometers. OCM differs from optical coherence tomography (OCT) in that i ...

2017

Just-in-time Analytics Over Heterogeneous Data and Hardware

Manolis Karpathiotakis

Industry and academia are continuously becoming more data-driven and data-intensive, relying on the analysis of a wide variety of datasets to gain insights. At the same time, data variety increases continuously across multiple axes. First, data comes in mu ...

EPFL2017

Program Analysis and Compilation Techniques for Speeding up Transactional Database Workloads

Mohammad Dashti Rahmat Abadi

There is a trend towards increased specialization of data management software for performance reasons. The improved performance not only leads to a more efficient usage of the underlying hardware and cuts the operation costs of the system, but also is a ga ...

EPFL2017

No data left behind: real-time insights from a complex data ecosystem

Anastasia Ailamaki, Manolis Karpathiotakis

The typical enterprise data architecture consists of several actively updated data sources (e.g., NoSQL systems, data warehouses), and a central data lake such as HDFS, in which all the data is periodically loaded through ETL processes. To simplify query p ...

2017

ReCache: Reactive Caching for Fast Analytics over Heterogeneous Data

Anastasia Ailamaki, Manolis Karpathiotakis, Tahir Azim

As data continues to be generated at exponentially growing rates in heterogeneous formats, fast analytics to extract meaningful information is becoming increasingly important. Systems widely use in-memory caching as one of their primary techniques to speed ...

2017

Building Efficient Query Engines using High-Level Languages

Ioannis Klonatos

We are currently witnessing a shift towards the use of high-level programming languages for systems development. These approaches collide with the traditional wisdom which calls for using low-level languages for building efficient software systems. This sh ...

EPFL2017

How to Architect a Query Compiler

Christoph Koch, Ioannis Klonatos, Amir Shaikhha, Lionel Emile Vincent Parreaux, Mohammad Dashti Rahmat Abadi, Lewis Alexander Brown

This paper studies architecting query compilers. The state of the art in query compiler construction is lagging behind that in the compilers field. We attempt to remedy this by exploring the key causes of technical challenges in need of well founded soluti ...

2016

Fast Queries Over Heterogeneous Data Through Engine Customization

Anastasia Ailamaki, Ioannis Alagiannis, Manolis Karpathiotakis

Industry and academia are continuously becoming more data-driven and data-intensive, relying on the analysis of a wide variety of heterogeneous datasets to gain insights. The different data models and formats pose a significant challenge on performing anal ...

Assoc Computing Machinery2016

How to Win a Hot Dog Eating Contest: Distributed Incremental View Maintenance with Batch Updates

Christoph Koch, Milos Nikolic, Mohammad Dashti Rahmat Abadi

In the quest for valuable information, modern big data applications continuously monitor streams of data. These applications demand low latency stream processing even when faced with high volume and velocity of incoming changes and the user’s desire to ask ...

2016

A Multiagent System for Dynamic Data Aggregation in Medical Research

Karl Aberer, Michael Ignaz Schumacher, Alevtina Dubovitskaya

The collection of medical data for research purposes is a challenging and long-lasting process. In an effort to accelerate and facilitate this process we propose a new framework for dynamic aggregation of medical data from distributed sources. We use agent ...

Hindawi Publishing Corporation2016

Efficient Incremental Data Analysis

Milos Nikolic

Many data-intensive applications require real-time analytics over streaming data. In a growing number of domains -- sensor network monitoring, social web applications, clickstream analysis, high-frequency algorithmic trading, and fraud detections to name a ...

EPFL2016